Multi-scenario simulation of carbon budget balance in arid and semi-arid regions.

The carbon budget has emerged as a central focus in global carbon cycle research. The limited understanding of carbon budget balance dynamics has led to an increasing imbalance between ecological and socio-economic benefits. Building upon a comprehensive analysis of carbon storage and emission in Lanzhou from 2000 to 2020, this study develops a novel deep learning model (CNN-LSTM) to simulate carbon budget under various scenarios from 2030 to 2050. Additionally, scientifically grounded recommendations for carbon compensation are provided. The results demonstrate several key findings: (1) The deep learning model exhibits outstanding performance, with an average overall accuracy exceeding 0.93. The coupled model outperforms individual models, underscoring the significance and necessity of incorporating both temporal and spatial features in land use simulation. (2) Under the ecological protection redline scenario from 2030 to 2050, a noteworthy augmentation in carbon storage and a proficient constraint on carbon emissions are observed. This substantiates the effectiveness of ecological protection interventions. (3) Carbon compensation payment areas are predominantly concentrated in built-up land, with the extent of these areas expanding over time. (4) The disparities in carbon balance effects of forest were more conspicuous than that of built-up land across diverse temporal and scenarios.

Divergent patterns and drivers of leaf functional traits of Robinia pseudoacacia and Pinus tabulaeformis plantations along a precipitation gradient in the Loess plateau, China.

Changes in precipitation patterns in arid and semi-arid regions can reshape plant functional traits and significantly affect ecosystem functions. However, the synchronous responses of leaf economical, anatomical, photosynthetic, and biochemical traits to precipitation changes and their driving factors have rarely been investigated, which hinders our understanding of plants' ecological adaptation strategies to drought tolerance in arid areas. Therefore, the leaf traits of two typical plantations (Robinia pseudoacacia, RP and Pinus tabulaeformis, PT) along the precipitation gradient in the Loess Plateau, including economical, anatomical, photosynthetic, and biochemical traits, were investigated in this study. The results show that the leaf photosynthetic traits of RP and PT increase along the precipitation gradient, whereas leaf biochemical traits decrease. The anatomical traits of PT decrease with increasing precipitation, whereas no significant variation was observed for RP. Random Forest analysis show that LNC, LDMC, Chl, and PRO are leaf traits that significantly vary with the precipitation gradient in both plantations. Correlation analysis reveals that the traits coordination of RP is better than that of PT. The LMG model was used to determine driving factors. The results suggest that MAP explains the variation of PT leaf traits better (30.38%-36.78%), whereas SCH and SPH contribute more to the variation of RP leaf traits (20.88%-41.76%). In addition, the piecewise Structural Equation Model shows that the climate and soil physical and chemical properties directly affect the selected leaf functional traits of RP, whereas only the soil chemical properties directly affect the selected leaf functional traits of PT. The results of this study contribute to the understanding of the ecological adaptation of plants to environmental gradients and highlight that correlations among leaf traits should be considered when predicting plant adaptation strategies under future global change scenarios.

Land-Use and Land-Cover Classification in Semi-Arid Areas from Medium-Resolution Remote-Sensing Imagery: A Deep Learning Approach.

Detailed Land-Use and Land-Cover (LULC) information is of pivotal importance in, e.g., urban/rural planning, disaster management, and climate change adaptation. Recently, Deep Learning (DL) has emerged as a paradigm shift for LULC classification. To date, little research has focused on using DL methods for LULC mapping in semi-arid regions, and none that we are aware of have compared the use of different Sentinel-2 image band combinations for mapping LULC in semi-arid landscapes with deep Convolutional Neural Network (CNN) models. Sentinel-2 multispectral image bands have varying spatial resolutions, and there is often high spectral similarity of different LULC features in semi-arid regions; therefore, selection of suitable Sentinel-2 bands could be an important factor for LULC mapping in these areas. Our study contributes to the remote sensing literature by testing different Sentinel-2 bands, as well as the transferability of well-optimized CNNs, for semi-arid LULC classification in semi-arid regions. We first trained a CNN model in one semi-arid study site (Gujranwala city, Gujranwala Saddar and Wazirabadtownships, Pakistan), and then applied the pre-trained model to map LULC in two additional semi-arid study sites (Lahore and Faisalabad city, Pakistan). Two different composite images were compared: (i) a four-band composite with 10 m spatial resolution image bands (Near-Infrared (NIR), green, blue, and red bands), and (ii) a ten-band composite made by adding two Short Wave Infrared (SWIR) bands and four vegetation red-edge bands to the four-band composite. Experimental results corroborate the validity of the proposed CNN architecture. Notably, the four-band CNN model has shown robustness in semi-arid regions, where spatially and spectrally confusing land-covers are present.

Rainwater harvesting and Leucaena leucocephala biomass rates effects on soil moisture, water use efficiency and Sorghum bicolor [(L.) Moench] productivity in a semi-arid area in Zimbabwe.

BACKGROUND: Sorghum is one of the major staple crops in Sub Saharan Africa but its production is mainly limited by moisture stress, frequent droughts and soil infertility, especially in the smallholder farming systems. This raises the need to develop climate smart options to improve sorghum production. The objective was to assess the effects of rainwater harvesting and use of different Leucaena leucocephala biomass rates on soil moisture content, rainwater use efficiency, and stover and grain yields in two sorghum varieties (Macia and SV1). The experiment was laid as a randomized complete block design in split-split plot arrangement from 2017/2018 to 2019/2020 season. RESULTS: The results show that tied contour (TC) and infiltration pits (IPs) significantly (P < 0.05) increased soil moisture content than standard contour (SC). Soil moisture content increased gradually with the increase in soil depth (20-40 cm > 0-20 cm), with 2018/2019 season having the maximum soil moisture content. Soil moisture content also increased with the increase in application rates of Leucaena biomass. Grain and stover yields were significantly (P < 0.05) increased by all Leucaena biomass application rates with higher yield observed in 2018/2019 season. SC had significantly lower grain and stover yields at all Leucaena biomass application rates. TC and IPs had comparable rainwater use efficiency compared to SC. Rainwater use efficiency increased with application rates of Leucaena biomass across all seasons and varieties. CONCLUSION: TC and IPs are better adaptive mechanisms against drought spells in semi-arid areas and can be combined with 10 t ha-1 of Leucaena biomass due to better yield increments realized. © 2022 Society of Chemical Industry.

Spatial Patterns of Soil Fungal Communities Are Driven by Dissolved Organic Matter (DOM) Quality in Semi-Arid Regions.

Soil fungi are ecologically important as decomposers, pathogens, and symbionts in nature. Understanding their biogeographic patterns and driving forces is pivotal to predict alterations arising from environmental changes in ecosystem. Dissolved organic matter (DOM) is an essential resource for soil fungi; however, the role of its quality in structuring fungal community patterns remains elusive. Here using Illumina MiSeq sequencing, we characterized total fungi and their functional groups in 45 soil samples collected from a 1500-km sampling transect through semi-arid regions in northern China, which are currently suffering great pressure from climate change. Total fungi and their functional groups were all observed to exhibit significant biogeographic patterns which were primarily driven by environmental variables. DOM quality was the best and consistent predictor of diversity of both total fungi and functional groups. Specifically, plant-derived DOM was associated with greater diversity relative to microbe-dominated origins. In addition, fungal diversity linearly increased with increases in degree of humification in DOM. Similarly, among all measured environmental variables, DOM quality had the strongest effects on the community composition of total fungi and functional groups. Together, our work contributes to the factors underlying fungal biogeographic patterns and adds detail to the importance of DOM quality in structuring fungal communities.

Soil wind erosion evaluation and sustainable management of typical steppe in Inner Mongolia, China.

Soil wind erosion is an important ecological environmental problem that is widespread in arid and semi-arid regions. Currently, related studies are mainly focused on spatiotemporal characteristics or analysis of effector mechanisms, and they do not facilitate direct servicing of management decisions. In this paper, we used the Xilingol typical steppe in Inner Mongolia, China, as a study site to develop a decision framework for a comprehensive understanding of soil wind erosion and to promote sustainable management of steppes. In this study, we used the Revised Wind Erosion Equation model to simulate soil wind erosion. We combined this model with linear trend analysis to evaluate the ecological effects of soil wind erosion and wind erosion intensity, and delineated the gravity center migration path. We used the constraint line method to reveal the mechanisms by which climatic factors affected soil wind erosion, achieved the spatial visualization of wind-breaking and sand-fixing service flow, and proposed decision-based regional sustainable development suggestions. The results showed that long-term soil wind erosion will lead to soil coarsening and loss of soil nutrients. Soil wind erosion in the study site showed worsening trends and risks, and as such, ecological environment conservation and management are urgently required. The study framework promotes a clear understanding of the complex relationship of human-earth systems. The study results will aid in the ecological remediation of steppe landscapes and the prevention of desertification and will provide a foundation for win-win management of ecological conservation and economic development in arid and semi-arid regions.

Evaluation of Sensible Heat Flux and Evapotranspiration Estimates Using a Surface Layer Scintillometer and a Large Weighing Lysimeter.

Accurate estimates of actual crop evapotranspiration (ET) are important for optimal irrigation water management, especially in arid and semi-arid regions. Common ET sensing methods include Bowen Ratio, Eddy Covariance (EC), and scintillometers. Large weighing lysimeters are considered the ultimate standard for measurement of ET, however, they are expensive to install and maintain. Although EC and scintillometers are less costly and relatively portable, EC has known energy balance closure discrepancies. Previous scintillometer studies used EC for ground-truthing, but no studies considered weighing lysimeters. In this study, a Surface Layer Scintillometer (SLS) was evaluated for accuracy in determining ET as well as sensible and latent heat fluxes, as compared to a large weighing lysimeter in Bushland, TX. The SLS was installed over irrigated grain sorghum (Sorghum bicolor (L.) Moench) for the period 29 July-17 August 2015 and over grain corn (Zea mays L.) for the period 23 June-2 October 2016. Results showed poor correlation for sensible heat flux, but much better correlation with ET, with r² values of 0.83 and 0.87 for hourly and daily ET, respectively. The accuracy of the SLS was comparable to other ET sensing instruments with an RMSE of 0.13 mm·h-1 (31%) for hourly ET; however, summing hourly values to a daily time step reduced the ET error to 14% (0.75 mm·d-1). This level of accuracy indicates that potential exists for the SLS to be used in some water management applications. As few studies have been conducted to evaluate the SLS for ET estimation, or in combination with lysimetric data, further evaluations would be beneficial to investigate the applicability of the SLS in water resources management.

Effects of Re-vegetation on Herbaceous Species Composition and Biological Soil Crusts Development in a Coal Mine Dumping Site.

Despite the critical roles of plant species' diversity and biological soil crusts (BSCs) in arid and semi-arid ecosystems, the restoration of the diversity of herbaceous species and BSCs are rarely discussed during the process of vegetation restoration of anthropogenically damaged areas in these regions. In this study, the herbaceous plant species composition, along with the BSCs coverage and thicknesses, was investigated at six different re-vegetation type sites, and the natural vegetation site of the Heidaigou open pit coal mine in China's Inner Mongolia Autonomous Region was used as a reference. The highest total species richness (16), as well as the species richness (4.4), occurred in the Tree and Herbaceous vegetation type site. The species composition similarities between the restored sites and the reference site were shown to be very low, and ranged from 0.09 to 0.42. Also, among the restored sites, the similarities of the species were fairly high and similar, and ranged from 0.45 to 0.93. The density and height of the re-vegetated woody plants were significantly correlated with the indexes of the diversity of the species. The Shrub vegetation type site showed the greatest total coverage (80%) of BSCs and algae crust coverage (48%). The Shrub and Herbaceous type had the greatest thicknesses of BSCs, with as much as 3.06 mm observed, which was followed by 2.64 mm for the Shrub type. There was a significant correlation observed between the coverage of the total BSCs, and the total vegetation and herbaceous vegetation coverage, as well as between the algae crust coverage and the herbaceous vegetation coverage. It has been suggested that the re-vegetated dwarf woody plant species (such as shrubs and semi-shrubs) should be chosen for the optimal methods of the restoration of herbaceous species diversity at dumping sites, and these should be planted with low density. Furthermore, the effects of vegetation coverage on the colonization and development the BSCs should be considered in order to reconstruct the vegetation in disturbed environments, such as mine dumpsites in arid areas.

Mapping Sub-surface Distribution of Soil Organic Carbon Stocks in South Africa's Arid and Semi-Arid Landscapes: Implications for Land Management and Climate Change Mitigation.

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Water periods impact the structure and metabolic potential of the nitrogen-cycling microbial communities in rivers of arid and semi-arid regions.

This study examined the influence of water periods on river nitrogen cycling by analysing nitrogen functional genes and bacterial communities in the Qingshui River, an upstream tributary of the Yellow River in China. Nitrate nitrogen predominated as inorganic nitrogen during the low-flow seasons, whereas salinity was highest during the high-flow seasons. Overall, the functional gene abundance increased with decreasing water volume, and nitrogen concentrations were determined by various specific gene groups. The relative abundance of bacteria carrying these genes varied significantly across water periods. The abundance of Pseudomona, Hydrogenophaga (carrying narGHI and nirB genes), and Flavobacterium (carrying nirK, norBC, and nosZ genes) significantly increased during the low-flow seasons. Nitrogen transformation bacteria exhibited both symbiotic and mutualistic relationships. Microbial network nodes and sizes decreased with decreasing water volume, whereas modularity increased. Additionally, the water period affected the functional microbial community structure by influencing specific environmental factors. Among them, SO42- primarily determined the denitrification, dissimilatory nitrate reduction to ammonium, and assimilatory nitrate reduction to ammonium communities, whereas NO2--N and Mg2+ were the main driving factors for the nitrogen-fixing and nitrifying communities, respectively. These findings have substantial implications for better understanding the reduction in river nitrogen loads in arid and semi-arid regions during different water periods.

Deterministic processes influence bacterial more than fungal community assembly during the development of biological soil crusts in the desert ecosystem.

Biological soil crusts (biocrusts) constitute a crucial biological component of the soil surface in arid and semi-arid ecosystems. Understanding the variations in soil microbial community assembly across biocrust successional stages is essential for a deeper comprehension of microbial biodiversity and desert ecosystem functioning. However, knowledge about the mechanisms of microbial community assembly and the factors influencing its development remains limited. In this study, we utilized amplicons sequencing to assess the compositions of bacterial and fungal communities in bare sand and three types of biocrusts (light cyanobacterial biocrusts, dark cyanobacterial biocrusts, and moss crusts). Subsequently, we analyzed the ecological processes shaping microbial community composition and structure, along with the influencing factors. Our results revealed a significant increase in bacterial diversity and no significant changes in fungal diversity during biocrust development. The relative abundances of the copiotrophic bacteria (e.g., Actinobacteria, Acidobacteria, and Bacteroidetes) showed significant increases, while oligotrophic bacteria (e.g., Proteobacteria and Firmicutes) decreased over time. Moreover, the relative abundances of Ascomycota, which exhibit strong resistance to adverse environmental conditions, significantly decreased, whereas Basidiomycota, known for their ability to degrade lignin, significantly increased throughout biocrust development. Additionally, stochastic processes (dispersal limitation and drift) predominantly drove the assemblies of both bacterial and fungal communities. However, the relative importance of deterministic processes (homogeneous selection) in bacterial assembly increased during biocrust development. Structural equation modeling indicated that bacterial community assembly was primarily related to soil water content, whereas fungal community assembly was primarily related to total organic carbon. These findings provide a scientific foundation for investigating the formation and development of biocrusts, and further insights into the conservation and sustainable management of biocrust resources under future climate change scenarios.

Intensified river salinization alters nitrogen-cycling microbial communities in arid and semi-arid regions of China.

Freshwater salinization is receiving increasing global attention due to its profound influence on nitrogen cycling in aquatic ecosystems and the accessibility of water resources. However, a comprehensive understanding of the changes in river salinization and the impacts of salinity on nitrogen cycling in arid and semi-arid regions of China is currently lacking. A meta-analysis was first conducted based on previous investigations and found an intensification in river salinization that altered hydrochemical characteristics. To further analyze the impact of salinity on nitrogen metabolism processes, we evaluated rivers with long-term salinity gradients based on in situ observations. The genes and enzymes that were inhibited generally by salinity, especially those involved in nitrogen fixation and nitrification, showed low abundances in three salinity levels. The abundance of genes and enzymes with denitrification and dissimilatory nitrate reduction to ammonium functions still maintained a high proportion, especially for denitrification genes/enzymes that were enriched under medium salinity. Denitrifying bacteria exhibited various relationships with salinity, while dissimilatory nitrate reduction to ammonium bacterium (such as Hydrogenophaga and Curvibacter carrying nirB) were more inhibited by salinity, indicating that diverse denitrifying bacteria could be used to regulate nitrogen concentration. Most genera exhibited symbiotic and mutual relationships, and the highest proportion of significant positive correlations of abundant genera was found under medium salinity. This study emphasizes the role of river salinity on environment characteristics and nitrogen transformation rules, and our results are useful for improving the availability of river water resources in arid and semi-arid regions.

Physical properties and mass models of Deglet Noor and Arichti semi-dry Algerian date fruits: A comparative study.

For thousands of years, date fruit (Phoenix dactylifera L.) has been a popular diet in arid and semi-arid locations. It has religious importance for Muslims and is especially important during the holy month of Ramadan. The global output of date fruits has been continuously expanding, with Arab nations accounting for a sizable portion. The emphasis of this research is on two popular semi-dry Algerian date fruit types, Deglet Noor and Arechti, which are grown in the Ziban region. These fruits' physical parameters, such as size, sphericity, surface area, volumes, and density, were determined. The goal of this study was to create a mass model based on these physical attributes to help in the grading and sorting of date fruits. Fruit mass was shown to be closely connected to linear dimensions, arithmetic and geometric mean diameters, surface area, and volumes. Correlations between mass and physical attributes were established using a variety of mathematical models, including linear, quadratic, S-curve, and power models. The results demonstrated the applicability of specific factors for mass modeling, offering useful insights for the development of system sizing and conservation. With good correlation, multivariate data analysis was employed to correctly estimate the mass of both kinds. This research advances our understanding of the physical features of Algerian date fruits and their connection to mass, allowing for better handling, sorting, and packing processes in the worldwide date market.

Integrated assessment of policy interventions for promoting sustainable irrigation in semi-arid environments: a hydro-economic modeling approach.

Sustaining irrigated agriculture to meet food production needs while maintaining aquatic ecosystems is at the heart of many policy debates in various parts of the world, especially in arid and semi-arid areas. Researchers and practitioners are increasingly calling for integrated approaches, and policy-makers are progressively supporting the inclusion of ecological and social aspects in water management programs. This paper contributes to this policy debate by providing an integrated economic-hydrologic modeling framework that captures the socio-economic and environmental effects of various policy initiatives and climate variability. This modeling integration includes a risk-based economic optimization model and a hydrologic water management simulation model that have been specified for the Middle Guadiana basin, a vulnerable drought-prone agro-ecological area with highly regulated river systems in southwest Spain. Namely, two key water policy interventions were investigated: the implementation of minimum environmental flows (supported by the European Water Framework Directive, EU WFD), and a reduction in the legal amount of water delivered for irrigation (planned measure included in the new Guadiana River Basin Management Plan, GRBMP, still under discussion). Results indicate that current patterns of excessive water use for irrigation in the basin may put environmental flow demands at risk, jeopardizing the WFD's goal of restoring the 'good ecological status' of water bodies by 2015. Conflicts between environmental and agricultural water uses will be stressed during prolonged dry episodes, and particularly in summer low-flow periods, when there is an important increase of crop irrigation water requirements. Securing minimum stream flows would entail a substantial reduction in irrigation water use for rice cultivation, which might affect the profitability and economic viability of small rice-growing farms located upstream in the river. The new GRBMP could contribute to balance competing water demands in the basin and to increase economic water productivity, but might not be sufficient to ensure the provision of environmental flows as required by the WFD. A thoroughly revision of the basin's water use concession system for irrigation seems to be needed in order to bring the GRBMP in line with the WFD objectives. Furthermore, the study illustrates that social, economic, institutional, and technological factors, in addition to bio-physical conditions, are important issues to be considered for designing and developing water management strategies. The research initiative presented in this paper demonstrates that hydro-economic models can explicitly integrate all these issues, constituting a valuable tool that could assist policy makers for implementing sustainable irrigation policies.

Cactus-sorghum intercropping combined with management interventions of planting density, row orientation and nitrogen fertilisation can optimise water use in dry regions.

Some strategies can optimise the use of water in crops under deficit, either by increasing yield or by reducing actual crop evapotranspiration (ET), to promote the sustainable intensification of production systems. The objective was to evaluate how the spacing, planting orientation, nitrogen fertilisation and intercropping strategies impact the dynamics of water in the soil, ET partitioning, and water use indicators for forage cactus and cactus-sorghum intercropping. Four experiments were conducted between 2018 and 2020 in the Brazilian semi-arid region. In the first two sites (I and II), the cladodes of the intercropped forage cactus and sorghum were spaced at 0.10, 0.20, 0.30, 0.40 and 0.50 m with rows-oriented east-west and north-south. In site III, the intercropped rows were spaced at 1.00, 1.25, 1.50 and 1.75 m. Site IV, which contained the forage cactus crop exclusively, was treated with four nitrogen levels (50, 150, 300 and 450 kg N ha-1). The management interventions improved water use more by increasing dry matter than by reducing ET in the cropping system. Intercropping promoted the greatest increase in water productivity (130 %). Increasing N doses in the forage cactus-only crop reduced ET by up to 39 % but increased deep drainage losses by up to 365 %. The most promising management practices for optimising water resources were as follows: spacing of 0.10 m between cactus plants in the intercropping trial under east-west row orientation, as it promoted greater water use efficiency (76 %); spacing of 0.30 m in the north-south orientation; and row spacing of 1.50 m, as it improved water productivity (6.89 kg m-3). Thus, interventions in management should be adopted to optimise water use in intercropping systems with forage cactus, aiming at sustainable intensification in dry environments.

Species mixing enhances the resistance of Robinia pseudoacacia L. to drought events in semi-arid regions: Evidence from China's Loess Plateau.

As a potential planting strategy, species mixing increases biomass production, improves ecosystem service functions, and mitigates climate change. However, the effect of species mixing on tree growth and drought resilience in semi-arid areas remains unclear. Hence, we established tree-ring chronologies of Robinia pseudoacacia L. in pure Robinia pseudoacacia L. plantation (RP) and mixed plantations with Hippophae rhamnoides L. and Populus simonii Carr. at different proportions of 8:2 and 5:5 (RH 8:2, RH 5:5, RC 8:2, RC 5:5) in the typical semi-arid region of the Loess Plateau (LP), China. The mean annual growth, climate-growth relationships, and tree resilience (Rs) to drought, including resistance (Rt) and recovery (Rc), were analyzed using dendrochronological methods. The results showed that the growth of R. pseudoacacia L. in mixed plantations was lower when Palmer Drought Severity Index (PDSI) >0, but much higher than that in monoculture under drought stress (PDSI <0 or after drought event). Meanwhile, the relationship between PDSI and tree growth was significantly positive in the pure plantation, but weakened in the mixed plantations, indicating that species mixing alleviated drought stress to some extent. The resilience results showed that, although the Rc was higher in monoculture after drought events, species mixing could enhance Rt and mitigate the growth decline of R. pseudoacacia L. during drought events. Moreover, the Rt varied significantly among mixing species and proportions and was also affected by the magnitude and timing of drought. The RC 5:5 and RH 8:2 had higher resistance to moderate and severe drought stress. However, RC 8:2 and RH 5:5 could cope better with mild drought stress. These results indicate that species mixing can alleviate drought stress and improve the drought resistance. Therefore, it is necessary to expand species mixing to maximize plantation functions and minimize the potential impacts of warming and drought in semi-arid regions.

Capillary rise induced salt deterioration on ancient wall paintings at the Mogao Grottoes.

Salt deterioration has been found to be a major threat to wall paintings at culture heritage sites in arid areas along the Silk Road. However, the routes of water migration that cause the efflorescence have not been identified, and consequently, effective preservation measures have not been developed. Our microanalysis, by interrogating 93,727 individual particles collected in a Mogao cave in Dunhuang, China, revealed that capillary rise of water in the earthen plasters drives the deterioration of wall paintings. The vertical distribution of chloride and sulfate particles in the salt efflorescence and their morphologies implied a migration of salts through capillary rise and subsequent crystal growth under environmental conditions exerts sufficient pressure to cause surface decay and loss. These results indicate that blocking the water capillary rise under the porous structures is likely the most effective route to prevent rapid deterioration of the ancient wall paintings. These salt transport and deterioration mechanisms in an arid environment, suggests that a wide range of management strategies and protective measures could be developed to effectively preserve heritage sites in arid regions, especially along the Silk Road.

Occurrence of Arbuscular Mycorrhizal Fungi in Rhizosphere of Jatropha curcas L. in Arid and Semi Arid Regions of India.

A study was conducted to identify common arbuscular mycorrhizal (AM) fungi present in rhizosphere of Jatropha curcas L., an important bio-diesel crop, from different arid and semi arid regions of India viz., Jodhpur (Rajasthan), Hissar (Haryana), Jhansi and Lalitpur (Uttar Pradesh) and Hyderabad (Andhra Pradesh). A total of 20 AM species were recorded, which consisted of two species of Acaulospora and 18 species of Glomus. The highest frequency of occurrence was recorded for Glomus intraradix (100%), followed by Acaulospora scrobiculata (83%), G. etunicatum (50%) and Glomus 1 (50%). Maximum species richness was recorded at Jodhpur, followed by Jhansi, Hissar, Hyderabad and Lalitpur. The results seem to suggest that species richness was more in arid regions as compared to semi arid areas.

Using different multivariate approaches to assess water quality of qanats in arid zones of Southern Central Mexico.

Qanats in the aquifer of the Tehuacán Valley (Mexico) represent an ancient way of using groundwater that is still practiced today. They are used mainly for agricultural irrigation. However, anthropogenic activities have jeopardized the use of these aquifers. We analyzed 24 qanats in the Tehuacán Valley to assess water quality. Based on 24 physicochemical variables, a water quality index (WQI) was constructed on a zero-to-100 scale, divided into five water quality classes. A decision-tree analysis was applied to identify the parameters with the highest influence on the WQI, considering the water quality classes as categorical responses and the values of physicochemical variables as drivers of these categories. We produced interpolation maps to identify trends. The relationship between the WQI and the normalized difference indices of vegetation and salinity (NDVI and NDSI, respectively) was analyzed using a ternary diagram. WQI scores showed that 12.5% of the qanats have very good quality; 25%, good quality; and the remaining (62.5%) range from moderate to unacceptable quality. The CHAID classification-tree method correctly explained 83.3% of the categories, with sulfates, alkalinity, conductivity, and nitrates as the main parameters that explain water quality. WQI was inversely related to NDVI and NDSI, showing seasonal differences. Interpolation maps suggest a better water quality in the northern zone of the aquifer.

Augmenting Leucaena leucocephala biomass with mineral fertiliser on rainwater use efficiency, agronomic efficiency and yields on sorghum (Sorghum bicolor [(L.) Moench]) under rainwater harvesting techniques in semi-arid region of Zimbabwe.

Food security in semi-arid regions is threatened by declining soil fertility, soil moisture stress and long frequent droughts as a result of erratic rainfall. Therefore we assessed the effects of augmenting Leucaena leucocephala biomass (organic manure) with mineral fertiliser on rainwater use efficiency, agronomic efficiency, grain and stover yields for two sorghum varieties (Macia and SV1) under rainwater harvesting techniques. The experiment was laid in split-split plot arrangement with rainwater harvesting method as main plot factor, with Leucaena biomass + NPK fertiliser as subplot factor and sorghum variety as sub-sub plot factor over three cropping seasons. Data collected include rainwater use efficiency, agronomic efficiency, grain and stover yields. Results show that tied contours have significantly (p ≤ 0.05) higher grain and stover yields from all varieties and seasons. Irregardless of sorghum variety, tied contours had significant (p ≤ 0.05) sorghum grain and stover yield followed by infiltration pits and lastly standard contours. Grain and stover yields improved with increasing levels of Leucaena biomass + NPK fertiliser combination. Highest grain yields observed were 1.146 t ha-1 (Macia) and 1.1 t ha-1 (SV1) from tied contour +15 t ha-1 biomass +150 kg ha-1 NPK fertiliser treatments. Rainwater use efficiency was significantly (p ≤ 0.05) higher from tied contours compared to infiltration pits and standard contour. Rainwater use efficiency was statistically (p ≤ 0.05) influenced by increasing application levels of Leucaena biomass + NPK fertiliser in all seasons. Agronomic efficiencies were considerably (p ≤ 0.05) affected by rainwater harvesting, Leucaena biomass + NPK fertiliser and interaction of all factors. It can therefore be concluded that Leucaena biomass + NPK fertiliser, tied contours and infiltration pits improve sorghum yields. Augmenting 2.5 t ha-1 biomass with 25 kg ha-1 NPK fertiliser under tied contours and Macia have better agronomic efficiency.